Software reliability analysis models
IBM Journal of Research and Development
Evaluation of competing software reliability predictions
IEEE Transactions on Software Engineering - Special issue on reliability and safety in real-time process control
Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
IEEE Transactions on Software Engineering
Recalibrating Software Reliability Models
IEEE Transactions on Software Engineering
“Fast learning in multi-resolution hierarchies”
Advances in neural information processing systems 1
Self organizing neural networks for the identification problem
Advances in neural information processing systems 1
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Software Reliability Models: Developments, Evaluation and Applications
Software Reliability Models: Developments, Evaluation and Applications
Using Neural Networks in Reliability Prediction
IEEE Software
Learning to Predict by the Methods of Temporal Differences
Machine Learning
Computational intelligence as an emerging paradigm of software engineering
SEKE '02 Proceedings of the 14th international conference on Software engineering and knowledge engineering
Optimal software release scheduling based on artificial neural networks
Annals of Software Engineering
Using Neural Networks in Reliability Prediction
IEEE Software
Parameter Estimation of the Manifold Growth Model Using Z-graph
METRICS '96 Proceedings of the 3rd International Symposium on Software Metrics: From Measurement to Empirical Results
Heuristic Self-Organization Algorithms for Software Reliability Assessment and Their Applications
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Using Machine Learning for Estimating the Defect Content After an Inspection
IEEE Transactions on Software Engineering
On-line prediction of software reliability using an evolutionary connectionist model
Journal of Systems and Software
Journal of Systems and Software
Predicting object-oriented software maintainability using multivariate adaptive regression splines
Journal of Systems and Software
Software reliability prediction by soft computing techniques
Journal of Systems and Software
An experimental study of adaptive testing for software reliability assessment
Journal of Systems and Software
Predicting software reliability with neural network ensembles
Expert Systems with Applications: An International Journal
Software Reliability Prediction Using Group Method of Data Handling
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Dependability metrics
Application of feed-forward neural networks for software reliability prediction
ACM SIGSOFT Software Engineering Notes
Assessment of software testing time using soft computing techniques
ACM SIGSOFT Software Engineering Notes
Support vector regression for software reliability growth modeling and prediction
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Enhancing software reliability estimates using modified adaptive testing
Information and Software Technology
Hybrid intelligent systems for predicting software reliability
Applied Soft Computing
Application of Machine Learning Techniques to Predict Software Reliability
International Journal of Applied Evolutionary Computation
A study on software reliability prediction models using soft computing techniques
International Journal of Information and Communication Technology
International Journal of Intelligent Systems Technologies and Applications
A survey of computational intelligence approaches for software reliability prediction
ACM SIGSOFT Software Engineering Notes
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The usefulness of connectionist models for software reliability growth prediction is illustrated. The applicability of the connectionist approach is explored using various network models, training regimes, and data representation methods. An empirical comparison is made between this approach and five well-known software reliability growth models using actual data sets from several different software projects. The results presented suggest that connectionist models may adapt well across different data sets and exhibit a better predictive accuracy. The analysis shows that the connectionist approach is capable of developing models of varying complexity.